Search Results (125)

The synergistic development of low-permeability reservoirs such as deep coalbed methane (CBM) and tight gas has emerged as a key technology to reduce development costs, enhance single-well productivity, and improve gas recovery. However, due to fundamental differences between coal seams and tight sandstones in their pore structure, permeability, water saturation, and pressure sensitivity, significant variations exist in their flow capacities and fluid production behaviors. To address the challenges of production allocation and main reservoir identification in the co-development of CBM and tight gas within deep gas-bearing basins, this study employs the transient multiphase flow simulation software OLGA to construct a representative dual-gas co-production well model. The regulatory mechanisms of the gas–liquid distribution, deliquification efficiency, and interlayer interference under two typical vertical stacking relationships—“coal over sand” and “sand over coal”—are systematically analyzed with respect to different tubing setting depths. A high-precision dynamic production allocation method is proposed, which couples the wellbore structure with real-time monitoring parameters. The results demonstrate that positioning the tubing near the bottom of both reservoirs significantly enhances the deliquification efficiency and bottomhole pressure differential, reduces the liquid holdup in the wellbore, and improves the synergistic productivity of the dual-reservoirs, achieving optimal drainage and production performance. Building upon this, a physically constrained model integrating real-time monitoring data—such as the gas and liquid production from tubing and casing, wellhead pressures, and other parameters—is established. Specifically, the model is built upon fundamental physical constraints, including mass conservation and the pressure equilibrium, to logically model the flow paths and phase distribution behaviors of the gas–liquid two-phase flow. This enables the accurate derivation of the respective contributions of each reservoir interval and dynamic production allocation without the need for downhole logging. Validation results show that the proposed method reliably reconstructs reservoir contribution rates under various operational conditions and wellbore configurations. Through a comparison of calculated and simulated results, the maximum relative error occurs during abrupt changes in the production capacity, approximately 6.37%, while for most time periods, the error remains within 1%, with an average error of 0.49% throughout the process. These results substantially improve the timeliness and accuracy of the reservoir identification. This study offers a novel approach for the co-optimization of complex multi-reservoir gas fields, enriching the theoretical framework of dual-gas co-production and providing technically adaptive solutions and engineering guidance for multilayer unconventional gas exploitation. Full article

Urban systems are the spatial carriers of social and economic relations at the regional level, and their relational and structural resilience are key to regional coordination and sustainable development, attracting widespread attention from scholars. In order to analyze the internal relationships of urban agglomerations in underdeveloped mountainous regions and optimize their spatial resource allocation and resilience, this study takes the urban agglomeration of Qiandongnan in China as an example and researches their internal relationships, development potential, and influencing factors based on quantitative methods such as social network analysis. The results show that the urban cluster in Qiandongnan presents “large dispersion and small aggregation” distribution characteristics, with the karst landscape as the main influencing factor; the spatial network exhibits a scale-free morphology with an obvious core–periphery structure, demonstrating moderate stability but poor completeness, weak equilibrium, and low overall resilience; only 15.61% of nodes demonstrate high competitiveness; urban units with functional roles serve as critical network nodes; urban units’ development potential is divided into three tiers (with 47.31% being medium-high), although overall levels remain low; and the development potential, overall network, individual network, and network resilience of urban units are all positively correlated, with economic and transportation development conditions being the main influencing factors. Based on the abovementioned findings, this study proposes a “multi-level resilience promotion path for network structure optimization”, which provides a theoretical basis and optimization control methods for the reconstruction and synergistic development of urban agglomerations. It also serves as a reference for the development planning of urban systems in other underdeveloped mountainous regions. Full article

Activating mutations in the epidermal growth factor receptor (EGFR) are key oncogenic drivers across multiple cancers, yet the structural mechanisms by which these mutations promote persistent receptor activation remain elusive. Here, we investigate how three clinically relevant mutations—T790M, L858R, and the T790M_L858R double mutant—reshape EGFR’s conformational ensemble and regulatory network architecture. Using multiscale molecular simulations and kinetic modeling, we show that these mutations, particularly in combination, enhance flexibility in the αC-helix and A-loop, favoring activation-competent states. Markov state modeling reveals a shift in equilibrium toward active macrostates and accelerated transitions between metastable conformations. To resolve the underlying coordination mechanism, we apply neural relational inference to reconstruct time-dependent interaction networks, uncovering the mutation-induced rewiring of allosteric pathways linking distant regulatory regions. This coupling of conformational redistribution with network remodeling provides a mechanistic rationale for sustained EGFR activation and suggests new opportunities for targeting dynamically organized allosteric circuits in therapeutic design. Full article

Array synthetic aperture radar (SAR) three-dimensional (3D) image reconstruction enables the extraction of target distribution information in 3D space, supporting scattering characteristic analysis and structural interpretation. SAR image reconstruction remains challenging due to issues such as noise contamination and incomplete echo data. By introducing sparse priors such as $L_1$ regularization functions, image quality can be improved to a certain extent and the impact of noise can be reduced. However, in scenarios involving distributed targets, the aforementioned methods often fail to maintain continuous structural features such as edges and contours, thereby limiting their reconstruction performance and adaptability. Recent studies have introduced geometric regularization functions to preserve the structural continuity of targets, yet these lack multi-prior consensus, resulting in limited reconstruction quality and robustness in complex scenarios. To address the above issues, a novel array SAR 3D reconstruction method based on multi-prior collaboration (ASAR-MPC) is proposed in this article. In this method, firstly, each optimization module in 3D reconstruction based on multi-prior is treated as an independent function module, and these modules are reformulated as parallel operations rather than sequential utilization. During the reconstruction process, the solution is constrained within the solution space of the module, ensuring that the SAR image simultaneously satisfies multiple prior conditions and achieves a coordinated balance among different priors. Then, a collaborative equilibrium framework based on Mann iteration is presented to solve the optimization problem of 3D reconstruction, which can ensure convergence to an equilibrium point and achieve the joint optimization of all modules. Finally, a series of simulation and experimental tests are described to validate the proposed method. The experimental results show that under limited echo and noise conditions, the proposed method outperforms existing methods in reconstructing complex target structures. Full article

In axisymmetric fusion devices like tokamaks, the winding of the magnetic field is characterized by its safety profile $q=q_{\mathbf{B}}$. Similarly, the winding of the current density field is characterized by $q_{\mathbf{J}}$. Currently, the relationship between $q_{\mathbf{B}}$ and $q_{\mathbf{J}}$ profiles and their effect on tokamak plasma confinement properties remains unexplored, as the $q_{\mathbf{J}}$ profile is neither computed nor considered. This study presents a reconstruction of the current density winding profile from experimental data in the quiescent H-mode. The topology analysis derived from $(q_{\mathbf{B}},q_{\mathbf{J}})$ was carried out using Hamada coordinates. It shows a large central plasma region unaffected by current filamentation-driven resonant magnetic perturbations, while the outer region harbors a spectrum of magnetic resonant modes, induced by current filaments located within the core plasma, which degrade peripheral confinement. These results suggest a QH-mode signature pattern needing further validation with additional data. Implementing $(q_{\mathbf{B}},q_{\mathbf{J}})$ real-time monitoring could provide insights into tokamak confinement regimes with significant implications. Full article

The widespread scrapping of retired mechanical parts has led to severe waste of resources and environmental burdens, posing a significant challenge to sustainable industrial development. To enable efficient recycling of retired mechanical parts and enhance the sustainability of their remanufacturing processes, the concept of biological genes is adopted to characterize the changes in the information of retired mechanical parts during the remanufacturing process as gene mutations of parts, aiming to maximize remanufacturing potential and devise an optimal generalized remanufacturing strategy for extending part life cycles. However, gene mutation of retired mechanical parts is not an isolated event. The modification of local genes may disrupt the original equilibrium of the part’s state, leading to conflicts such as material–performance, structure–function/performance, and function–performance. These conflicts constitute a major challenge and bottleneck in designing generalized remanufacturing schemes. Therefore, we propose a conflict identification and resolution method for gene mutation of retired mechanical parts. First, gene mutation graph of retired mechanical parts is established to express its all-potential remanufacturing pathways. Using discrimination rules and the element representation method from extenics, mutation conflicts are identified, and a conflict problem model is constructed. Then, the theory of inventive problem solving (TRIZ) engineering parameters are reconstructed and mapped to the mutation conflict parameters. The semantic mapping between the inventive principles and the transforming bridges is established by the Word2Vec algorithm, thereby improving the transforming bridge method to generate conflict resolution solutions. A coexistence degree function of transforming bridges is proposed to verify the feasibility of the resolution solutions. Finally, taking the generalized remanufacturing of a retired gear shaft as an example, we analyze and discuss the process and outcome of resolving gene mutation conflicts, thereby verifying the feasibility and effectiveness of the proposed concepts and methodology. Full article

Molecular network conformations in the over-stoichiometric arsenoselenides of canonical As_xSe_100−x system (40 ≤ x ≤ 100) covering a full row of thioarsenide-type As₄Se_n entities (0 ≤ n ≤ 6) are analyzed with ab initio quantum-chemical modeling employing cluster-simulation code CINCA. Native (melt-quenching-derived) and nanostructurization-driven (activated by nanomilling) polymorphic and polyamorphic transitions initiated by decomposition of the thioarsenide-type As₄Se_n cage molecules and incorporation of their remnants into a newly polymerized arsenoselenide network are identified on the developed map of molecular network clustering in a binary As-Se system. Within this map, compositional counter lines corresponding to preferential molecular or network-forming tendencies in the examined arsenoselenides are determined, explaining that network-crystalline conformations prevail in the boundary compositions corresponding to n = 6 and n = 0, while molecular-crystalline ones dominate inside the rows corresponding to n = 4 and n = 3. A set of primary and secondary equilibrium lines is introduced in the developed clustering map to account for inter-phase equilibria between the most favorable (regular) and competitive (irregular) thioarsenide phases. Straightforward interpretation of decomposition reactions accompanying induced crystallization and amorphization (reamorphization) in the arsenoselenides is achieved, employing disproportionality analysis of thioarsenide-type molecular network conformations within the reconstructed clustering map. The preference of network clustering at the boundaries of the As₄Se_n row (at n = 6 and n = 0) disturbs inter-phase equilibria inside this row, leading to unexpected anomalies, such as absence of stable tetra-arsenic triselenide As₄Se₅ molecular-crystalline species; polyamorphism in mechanoactivated As₄Se_n alloys (2 ≤ n ≤ 6); breakdown in the glass-forming ability of melt-quenching-derived arsenoselenides in the vicinity of tetra-arsenic biselenide As₄Se₂ composition; plastically and normally crystalline polymorphism in tetra-arsenic triselenide As₄Se₃-based thioarsenides, and so on. Full article

Understanding glacier and climate variations since pre-Industrial times is crucial for evaluating the present-day glacier response to climate change. Here, we focus on twelve small glaciers (≤2.0 km²) on both the northern and southern slopes of the Greater Caucasus to assess post-Little Ice Age glacier–climate fluctuations in this region. We reconstructed the Little Ice Age glacier extent using a manual detection method based on moraines. More recent glacier fluctuations were reconstructed using historical topographical maps and satellite imagery. Digital elevation models were used to estimate the topographic characteristics of glaciers. We also used the accumulation area ratio (AAR) method and a regional temperature lapse rate to reconstruct glacier snowlines and corresponding temperatures since the 1820s. The results show that all selected glaciers have experienced area loss, terminus retreat, and equilibrium line altitude (ELA) uplift over the last 200 years. The total area of the glaciers has decreased from 19.1 ± 0.9 km² in the 1820s to 9.7 ± 0.2 km² in 2020, representing a −49.2% loss, with an average annual reduction of −0.25%. The most dramatic reduction occurred between the 1960s and 2020, when the glacier area shrank by −35.5% or −0.59% yr⁻¹. The average terminus retreat for all selected glaciers was −1278 m (−6.4 m/yr⁻¹) during the last 200 years, while the average retreat over the past 60 years was −576 m (−9.6 m/yr⁻¹). AAR-based (0.6 ± 0.05) ELA reconstructions from all twelve glaciers suggest that the average ELA in the 1820s was about 180 m lower (3245 ± 50 m a.s.l.) than today (3425 ± 50 m a.s.l.), corresponding to surface air temperatures <1.1 ± 0.3 °C than today (2001–2020). The largest warming occurred between the 1960s and today, when snowlines rose by 105 m and air temperatures increased by <0.6 ± 0.3 °C. This study represents a first attempt at using glacier evidence to estimate climate changes in the Caucasus region since the Little Ice Age, and it can be used as a baseline for future studies. Full article

Understanding the feedback relationships and evolutionary stages of water–socioecological systems (W-SESs) is crucial for achieving sustainable development in basins. This study focuses on the Lake Victoria Basin (LVB) in East Africa, where population growth, rapid urbanization, and developing industrialization have intensified water resource supply–demand conflicts, leading to socioecological issues such as water environmental degradation and ecological conflicts. The objective of this research is to develop a theoretical framework for the Lake Victoria Basin W-SESs (LVB-WSESs) based on the SES framework, identify the main drivers and critical nodes in the evolution of the LVB-WSESs, analyze the root causes of water–society–ecology conflicts, and explore the feedback relationships and evolutionary stages of the LVB-WSESs over the past century. To achieve this, we employed an integrated qualitative and quantitative analysis of historical data combined with tipping point detection to systematically assess the dynamics of the LVB-WSESs. Our findings show that, under the drivers of climate change (with a 1 °C increase in annual temperature since 1920s), population growth (a six-fold increase since 1920s), economic development, land-use change, urbanization, and species invasion, the basin’s demand for water resources, water environments, and aquatic ecosystems has continually increased, leading to the gradual degradation and imbalance of the basin’s ecological functions. The evolution of the LVB-WSESs can be divided into five stages against the historical backdrop of societal transitions from colonial to independent democratic systems: the stable resource utilization period, the slow environmental change period (1920s–1960s), the rapid environmental imbalance period (1960s–1990s), the transition period from environmental imbalance to protection (1990s–2015), and the reconstruction period of socioecological equilibrium. This study not only enhances understanding of the long-term dynamics of the LVB-WSESs but also provides practical implications for sustainable water management in similar basins globally. It enriches the local practice of global sustainable development theories, providing new theoretical perspectives and case references for future watershed sustainable management. By identifying critical drivers and evolutionary stages, our findings can inform policy decisions and interventions to mitigate socioecological conflicts and achieve basin-level sustainability. Full article

In the present study, abilities of various macroscopic models (Navier–Stokes–Fourier, Burnett, original and regularized Grad’s 13-moment equations) in predicting the nonequilibrium molecular velocity distribution are examined. The results of the local distribution function reconstruction from flow macroparameters for the models considered are compared with each other and with the reference solution. Two different flows are considered: normal shock wave and stationary regular reflection of oblique shock waves. The Direct Simulation Monte Carlo method is used to obtain the reference solution and the flow macroparameters required for the distribution function reconstruction. All models under consideration predict the distribution function in the upstream low-density region rather poorly, with strong oscillations and unphysical negative values (especially regularized Grad’s 13-moment equations). In the high-density downstream region, the shape of the reference distribution is close to equilibrium, and all macroscopic models predict it rather accurately. Full article

For an extended lattice Boltzmann model based on a product-form equilibrium distribution function, an improved regularization model with enhanced numerical stability is proposed. In this paper’s regularized collision model, coefficients are calculated using two distinct methods during the reconstruction of the non-equilibrium distribution. The first method stems from the direct projection of the non-equilibrium distribution, while the second method relies on the regularization step, which is refined through the recursive calculation of the coefficients of non-equilibrium Hermite polynomials. Compared to the original lattice Boltzmann model, the recursive regularization method significantly enhances the stability of the numerical scheme by appropriately filtering out second-order and/or higher-order non-hydrodynamic contributions. Initially, under isothermal conditions, the periodic double-shear layer simulations are conducted at Reynolds numbers ranging from 10⁴ to 10⁶, testing the enhanced effect of the regularized model in broadening its available speed range. Subsequently, with a fixed Reynolds number, simulations are performed at various temperature values to assess the model’s performance when deviating from the lattice reference temperature. The results demonstrate that, compared to the original model, the recursive regularization model exhibits improved stability and widens the model’s usable speed and temperature ranges. Full article

Purpose—The reconstruction of worn-out urban fabrics poses a significant challenge in sustainable urban development, as such places, due to their decay and infrastructural inefficiencies, diminish residents’ quality of life and generate many environmental, social, and economic issues. Meanwhile, green building techniques have emerged as a novel option because they focus on environmental sustainability and resource efficiency. Nonetheless, effectively executing these strategies in worn-out urban fabrics necessitates a thorough feasibility evaluation to identify the associated obstacles and implementation prerequisites. The current study aimed to identify critical indicators for the feasibility of employing contemporary green building techniques in the repair of worn-out urban fabrics in Iran. The revitalization of worn-out urban fabrics is essential to enhancing the quality of life of urban inhabitants. Regarding this matter, the concept of green buildings, which emphasizes environmental sustainability, deserves significant attention. Meanwhile, feasibility assessments can help to successfully implement these changes in worn-out urban fabrics. Accordingly, the current study seeks to determine the essential indicators for the feasibility assessment of using initiative green building methods in the revitalization of worn-out urban fabric. Design/methodology/approach—In this vein, two rounds of the Delphi survey technique were carried out to identify and consolidate the indicators for the feasibility assessment of using initiative green building methods in the revitalization of the worn-out urban fabric in Iran. A research questionnaire was developed after reviewing the literature. It consists of four main dimensions (i.e., environmental, cultural–social, management–legal, and technical–technological) containing a total of 26 distinct indicators. The questionnaire was distributed among 123 experienced specialists. Eventually, the collected data were analyzed using the SPSS and Smart PLS programs. Findings—The results revealed that identified dimensions and indicators can be considered significant and essential indices in evaluating the use of initiative green building methods in the revitalization of worn-out urban fabric. Furthermore, the sequence of importance of the dimensions was environmental, followed by technical and technological, cultural and social, and managerial and legal. The environment, with an average rating of 3.33, ranked first; technical–technology, with an average rating of 2.45, ranked second; cultural–social, with an average rating of 2.15, ranked third; and management–legal, with an average rating of 2.07, ranked fourth. Furthermore, among the ranked indicators, the utilization of natural plants as a source of inspiration for living design in communal areas, aimed at toxin absorption and gas mitigation while achieving thermal equilibrium, received the highest average rating of 18.22, securing the first position. Conversely, the indicator assessing residents’ financial capacity, and the establishment of executive assurances and governmental support for the revitalization of the neighborhoods’ fabric garnered the lowest average rating of 10.98, placing it 26th and final. Originality/value—This research’s findings can significantly influence public policy and urban planning initiatives, aiding in the sustainable repair of worn-out urban fabrics in Iran by offering a systematic framework for evaluating the viability of innovative green building techniques. Full article

Geothermal energy has the advantages of being green, stable, abundant, and renewable. The thermal energy extraction efficiency of an enhanced geothermal system (EGS) is significantly regulated by Thermo–Hydraulic (TH) processes. To accurately evaluate the long-term heat recovery performance of an EGS, the dynamic influence mechanisms under multi-field TH coupling effects must be considered comprehensively. Therefore, in this study, based on the local thermal equilibrium theory, a temperature–seepage coupling model is established using the COMSOL software. The influences of reservoir parameters and fractures on the geothermal energy mining effect are studied, and the distribution law of temperature and pressure in the thermal reservoir is analyzed. The research results provide a reference for EGS reservoir reconstruction and heat recovery efficiency optimization. It is shown that the temperature difference near the injection–production well in the early stage of development leads to the slow recovery of thermal reservoir pressure. When the matrix permeability is greater than 455 mD, the temperature of the production fluid drops too quickly, and the development life of the thermal reservoir is short. The matrix porosity has little effect on the development of thermal reservoirs. When the porosity increases from 0.05 to 0.3, after 40 years of production, the mass flow rate of the produced fluid increases by 3.08%, the temperature of the produced fluid increases by 2.14%, and the heat recovery rate increases by 7.04%. The number of fractures has a significant influence on the development of thermal reservoirs. When the number of fractures increases from 0 to 3, the mass flow rate of production fluid increases by 55.9%, the thermal breakthrough is rapid, and the development life of the thermal reservoir is shortened. Notably, the unreasonable use of cracks will hinder the outward spread of the injected fluid. Full article

This paper presents a meshless Galerkin method for analyzing the nonlinear behavior of corrugated sandwich plates. A corrugated sandwich plate is a composite structure comprising two flat face sheets and a corrugated core, which can be approximated as an orthotropic anisotropic plate with distinct elastic properties in two perpendicular directions. The formulation is based on the first-order shear deformation theory (FSDT), where the shape functions are constructed using the moving least-square (MLS) approximation. Nonlinear stress and strain expressions are derived according to von Kármán’s large deflection theory. The virtual strain energy functionals of the individual plates are established, and their nonlinear equilibrium equations are formulated using the principle of virtual work. The governing equations for the entire corrugated sandwich structure are obtained by incorporating boundary conditions and displacement continuity constraints. A Newton–Raphson iterative scheme is employed to solve the nonlinear equilibrium equations. The computational program is implemented in C++, and extensive numerical examples are analyzed. The accuracy and reliability of the proposed method are validated through comparisons with ANSYS finite element solutions using SHELL181 elements. The method used in this paper can avoid the problems of mesh reconstruction and mesh distortion in the finite element method. In practical application, it simplifies the simulation calculation and understands the mechanical behavior of sandwich plates closer to actual engineering practice. Full article

After 35 years of a free market in Poland, three life insurance companies have gained a dominant position in the market and developed certain procedural equilibrium in the area of training, allowing their status quo to be maintained. Yet, they do not take into account the opinions of agents and the possibility of using the latest IT developments, including artificial intelligence, which supports increasingly broad areas of activity in organisations with great success. As independent sales force training poses a challenge to any national or multinational company in a constantly changing global economy, the primary focus of this research was to analyse the opinions of the top 438 agents from dominant life insurance companies. A need was emphasised to reconfigure the existing training programmes with the potential for AI involvement to achieve a more effective educational trajectory. The research findings confirmed the necessity to reconstruct training programmes in relation to an agent’s age, education level, and seniority and offered grounds for discussing innovative AI concepts that can be relevant for future academic research in management sciences and improving organisational effectiveness, particularly in life insurance companies or other first-contact personnel-dependent institutions. Full article